Artificial intelligence systems for quantifying movement disorder symptoms and adjusting treatment based on symptom quantification

Abstract

The present invention relates to methods for remotely and intelligently tuning movement disorder of therapy systems. The present invention still further provides methods of quantifying movement disorders for the treatment of patients who exhibit symptoms of such movement disorders including, but not limited to, Parkinson's disease and Parkinsonism, Dystonia, Chorea, and Huntington's disease, Ataxia, Tremor and Essential Tremor, Tourette syndrome, stroke, and the like. The present invention yet further relates to methods of remotely and intelligently or automatically tuning a therapy device using objective quantified movement disorder symptom data to determine the therapy setting or parameters to be transmitted and provided to the subject via his or her therapy device. The present invention also provides treatment and tuning intelligently, automatically and remotely, allowing for home monitoring of subjects.

What is claimed: 
     
       1. A movement disorder symptom quantification system comprising:
 at least one movement sensor adapted to acquire movement data related to a first subject's external body motion while the subject performs activities of daily living that are not performed according to direction or instruction or as a directed task; and 
 a processor comprising an algorithm adapted to calculate a quantification score of at least one symptom based at least in part on the acquired movement data, 
 wherein the algorithm is trained at least in part on reference data of the first subject and/or other subjects, the reference data comprising:
 movement data collected using at least one movement sensor corresponding to the first subject's and/or other subjects' movement, and at least one type of data from the group consisting of: 
 video data collected with a video sensor adapted to collect video data corresponding to the first subject's and/or other subjects' movement, 
 clinician scores corresponding to the first subject's and/or other subjects' movement, and 
 treatment parameters for the first subject and/or other subjects corresponding to the first subject's or other subjects' movement. 
 
 
     
     
       2. The system of  claim 1 , wherein the movement data collected using at least one movement sensor corresponding to the first subject's and/or other subjects' movement of the reference data is time correlated with at least one of the video data, clinician scores, and/or treatment scores of the reference data. 
     
     
       3. The system of  claim 2 , wherein the algorithm comprises an artificial neural network and/or a genetic algorithm. 
     
     
       4. The system of  claim 2 , further comprising an algorithm output adapted for outputting the calculated score or data related to the calculated score and for adjusting treatment parameters or settings of a treatment device or drug dosage. 
     
     
       5. The system of  claim 4 , wherein the treatment device is a deep brain stimulation (DBS) device. 
     
     
       6. The system of  claim 4 , wherein the treatment device is a pharmaceutical or drug delivery device. 
     
     
       7. The system of  claim 4 , wherein subject or a clinician adjusts a subject's self-administered drug dosage based on the algorithm output. 
     
     
       8. A movement disorder symptom quantification and treatment system comprising:
 at least one movement sensor adapted to acquire movement data related to a first subject's external body motion while the subject performs activities of daily living that are not performed according to direction or instruction or as a directed task; 
 a processor comprising an algorithm adapted to calculate a quantification score of at least one symptom based at least in part on the acquired movement data; 
 an algorithm output adapted for outputting the calculated score or data related to the calculated score; and 
 a treatment device adapted to receive the algorithm output and to adjust treatment parameters or settings based at least in part on the algorithm output, 
 wherein the algorithm is trained at least in part on reference data of the first subject and/or other subjects, the reference data comprising:
 movement data collected using at least one movement sensor corresponding to the first subject's and/or other subjects' movement, and at least one type of data from the group consisting of: 
 video data collected with a video sensor adapted to collect video data corresponding to the first subject's and/or other subjects' movement, 
 clinician scores corresponding to the first subject's and/or other subjects' movement, and 
 treatment parameters for the first subject and/or other subjects corresponding to the first subject's or other subjects' movement. 
 
 
     
     
       9. The system of  claim 8 , wherein the movement data collected using at least one movement sensor corresponding to the first subject's and/or other subjects' movement of the reference data is time correlated with at least one of the video data, clinician scores, and/or treatment scores of the reference data. 
     
     
       10. The system of  claim 9 , wherein the algorithm comprises an artificial neural network and/or a genetic algorithm. 
     
     
       11. The system of  claim 9 , wherein the treatment device is adapted to be adjusted automatically based at least in part on the algorithm output. 
     
     
       12. The system of  claim 11 , wherein the treatment device is a deep brain stimulation (DBS) device. 
     
     
       13. The system of  claim 11 , wherein the treatment device is a pharmaceutical or drug delivery device. 
     
     
       14. A movement disorder symptom quantification and treatment system comprising:
 at least one movement sensor adapted to acquire movement data related to a first subject's external body motion while the subject performs activities of daily living that are not performed according to direction or instruction or as a directed task; 
 a processor comprising an algorithm adapted to calculate a quantification score of at least one symptom based at least in part on the acquired movement data; and 
 an algorithm output adapted for outputting the calculated score or data related to the calculated score and for adjusting treatment parameters or settings of a treatment device or drug dosage; and 
 wherein the algorithm is trained at least in part on reference data of the first subject and/or other subjects, the reference data comprising:
 movement data collected using at least one movement sensor corresponding to the first subject's and/or other subjects' movement, and at least one type of data from the group consisting of: 
 video data collected with a video sensor adapted to collect video data corresponding to the first subject's and/or other subjects' movement, 
 clinician scores corresponding to the first subject's and/or other subjects' movement, and 
 treatment parameters for the first subject and/or other subjects corresponding to the first subject's or other subjects' movement. 
 
 
     
     
       15. The system of  claim 14 , wherein the movement data collected using at least one movement sensor corresponding to the first subject's and/or other subjects' movement of the reference data is time correlated with at least one of the video data, clinician scores, and/or treatment scores of the reference data. 
     
     
       16. The system of  claim 15 , wherein the algorithm comprises an artificial neural network and/or a genetic algorithm. 
     
     
       17. The system of  claim 15 , wherein the treatment device is adapted to be adjusted automatically based at least in part on the algorithm output. 
     
     
       18. The system of  claim 17 , wherein the treatment device is a deep brain stimulation (DBS) device. 
     
     
       19. The system of  claim 17 , wherein the treatment device is a pharmaceutical or drug delivery device. 
     
     
       20. The system of  claim 16 , wherein the subject or a clinician adjusts a subject's self-administered drug dosage based on the algorithm output.